The opticlust algorithm yielded high quality OTUs based on the high precision metrics below.
| Parameter | Value |
|---|---|
| cutoff | 0.2 |
| Sensitivity | 0.998 |
| Specificity | 0.999 |
| PPV | 0.998 |
| NPV | 0.999 |
| Accuracy | 0.999 |
| MCC | 0.997 |
| F1score | 0.998 |
| FDR | 0.002 |
The taxonomy assignment is based on the phylotype method in mothur platform. Only taxon observed more than once are displayed.
Figure x: Unfiltered and curated OTU abundance. Visual representation of taxon terms highlight the most abundant taxon based on frequency of being assigned to an OTU or tree nodes. Muribaculaceae is the most frequently assigned family and Muribaculaceae_ge is the most frequent species assigned to most sequences.
OTUs
[1] "Otu01" "Otu02" "Otu03" "Otu04" "Otu05" "Otu06" "Otu08" "Otu09"
[9] "Otu10" "Otu18"
Phylum
[1] "Bacteroidetes" "Firmicutes"
Class
[1] "Bacteroidia" "Clostridia"
Order
[1] "Bacteroidales" "Clostridiales" "Lactobacillales"
Family
[1] "Bacteroidaceae" "Lachnospiraceae" "Muribaculaceae" "Ruminococcaceae"
Genus
[1] "Alistipes" "Bacteroides" "Lactobacillus"
[4] "Mollicutes_RF39_ge" "Muribaculaceae_ge" "Oscillospira"
[7] "Turicibacter"
Figure x. Rank abundance of eight samples. Package: goeveg
Figure x. Correlation between species identified at phylum-level. Species are ordered alphabetically (top panel) and heuristically (bottom panel)
Figure x: Stacked barplots for species richness. The estimated richness (green bars) was calculated using chao calculator and observed ichness (red bars) was calculated using sobs.
Figure x: Species richness (observed species) displayed by boxplot (A), density plots (B) and histograms (C).
Include are:
OTUbased
Number_clusters Value_Index
3.0000 1.9922
Phylum
Number_clusters Value_Index
3.0000 4.9398
Class
Number_clusters Value_Index
3.0000 4.2837
Order
Number_clusters Value_Index
3.000 3.667
Family
Number_clusters Value_Index
2.0000 3.0988
Genus
Number_clusters Value_Index
3.0000 2.3948
Square root transformation
Wisconsin double standardization
Run 0 stress 0.02311505
Run 1 stress 0.02438405
Run 2 stress 0.02311359
... New best solution
... Procrustes: rmse 0.0005183599 max resid 0.0007295316
... Similar to previous best
Run 3 stress 0.0004584523
... New best solution
... Procrustes: rmse 0.1483403 max resid 0.2621175
Run 4 stress 9.860654e-05
... New best solution
... Procrustes: rmse 0.04889454 max resid 0.07544724
Run 5 stress 0.02226818
Run 6 stress 9.69273e-05
... New best solution
... Procrustes: rmse 0.001965716 max resid 0.003977862
... Similar to previous best
Run 7 stress 9.999656e-05
... Procrustes: rmse 0.08246718 max resid 0.1334889
Run 8 stress 0.02226872
Run 9 stress 0.02438409
Run 10 stress 0.0004451715
... Procrustes: rmse 0.1210363 max resid 0.1955044
*** Solution reached
Square root transformation
Wisconsin double standardization
Run 0 stress 5.792227e-06
Run 1 stress 0.09233043
Run 2 stress 0.2004274
Run 3 stress 9.882603e-05
... Procrustes: rmse 0.05899969 max resid 0.1129256
Run 4 stress 9.81698e-05
... Procrustes: rmse 0.05810476 max resid 0.08380598
Run 5 stress 0.06988752
Run 6 stress 9.901129e-05
... Procrustes: rmse 0.08357369 max resid 0.1174309
Run 7 stress 9.92299e-05
... Procrustes: rmse 0.07699285 max resid 0.122011
Run 8 stress 9.975641e-05
... Procrustes: rmse 0.13685 max resid 0.202801
Run 9 stress 0.1448684
Run 10 stress 9.132325e-05
... Procrustes: rmse 0.04390869 max resid 0.07203059
Run 11 stress 0.0001132911
... Procrustes: rmse 0.1273508 max resid 0.1978526
Run 12 stress 9.786936e-05
... Procrustes: rmse 0.1216092 max resid 0.1935745
Run 13 stress 9.26535e-05
... Procrustes: rmse 0.05651613 max resid 0.1103798
Run 14 stress 0.06988741
Run 15 stress 9.423633e-05
... Procrustes: rmse 0.1405515 max resid 0.2836626
Run 16 stress 8.171376e-05
... Procrustes: rmse 0.0624041 max resid 0.09980293
Run 17 stress 9.507963e-05
... Procrustes: rmse 0.05671056 max resid 0.08367146
Run 18 stress 9.942293e-05
... Procrustes: rmse 0.05752394 max resid 0.09767716
Run 19 stress 0.0003890592
... Procrustes: rmse 0.1387151 max resid 0.208923
Run 20 stress 9.977772e-05
... Procrustes: rmse 0.1185833 max resid 0.1793281
*** No convergence -- monoMDS stopping criteria:
2: no. of iterations >= maxit
13: stress < smin
5: stress ratio > sratmax
Square root transformation
Wisconsin double standardization
Run 0 stress 0.001418859
Run 1 stress 0.00141893
... Procrustes: rmse 2.590167e-05 max resid 3.969124e-05
... Similar to previous best
Run 2 stress 0.05061396
Run 3 stress 0.001418881
... Procrustes: rmse 4.112065e-05 max resid 6.294641e-05
... Similar to previous best
Run 4 stress 0.1108941
Run 5 stress 0.001418859
... New best solution
... Procrustes: rmse 1.216135e-06 max resid 1.548384e-06
... Similar to previous best
Run 6 stress 0.1513699
Run 7 stress 0.001418878
... Procrustes: rmse 1.158292e-05 max resid 1.778304e-05
... Similar to previous best
Run 8 stress 0.1727749
Run 9 stress 0.001418908
... Procrustes: rmse 2.245688e-05 max resid 3.426386e-05
... Similar to previous best
Run 10 stress 0.1319101
*** Solution reached
Square root transformation
Wisconsin double standardization
Run 0 stress 0.02218756
Run 1 stress 0.02218377
... New best solution
... Procrustes: rmse 0.0009434361 max resid 0.001323574
... Similar to previous best
Run 2 stress 0.02218658
... Procrustes: rmse 0.0007002663 max resid 0.0009812776
... Similar to previous best
Run 3 stress 0.02217476
... New best solution
... Procrustes: rmse 0.003355352 max resid 0.004665514
... Similar to previous best
Run 4 stress 0.02223982
... Procrustes: rmse 0.01210337 max resid 0.01706141
Run 5 stress 0.02217595
... Procrustes: rmse 0.002522356 max resid 0.003498614
... Similar to previous best
Run 6 stress 0.0221821
... Procrustes: rmse 0.002897763 max resid 0.00402172
... Similar to previous best
Run 7 stress 0.08213731
Run 8 stress 0.02226069
... Procrustes: rmse 0.01428661 max resid 0.01999361
Run 9 stress 0.08244629
Run 10 stress 0.02217762
... Procrustes: rmse 0.001403351 max resid 0.001944862
... Similar to previous best
*** Solution reached
Square root transformation
Wisconsin double standardization
Run 0 stress 0.0005606845
Run 1 stress 0.01736873
Run 2 stress 0.005096509
Run 3 stress 0.0008738854
... Procrustes: rmse 0.1006689 max resid 0.1706016
Run 4 stress 0.00138802
Run 5 stress 0.0001893003
... New best solution
... Procrustes: rmse 0.03750972 max resid 0.05272904
Run 6 stress 0.01750833
Run 7 stress 0.01747092
Run 8 stress 0.01832696
Run 9 stress 0.01832654
Run 10 stress 0.001450898
Run 11 stress 0.01832641
Run 12 stress 8.579538e-05
... New best solution
... Procrustes: rmse 0.01696292 max resid 0.0327858
Run 13 stress 0.002567052
Run 14 stress 0.01768765
Run 15 stress 0.002013325
Run 16 stress 0.01756597
Run 17 stress 0.01832713
Run 18 stress 0.00161634
Run 19 stress 0.01520625
Run 20 stress 0.01832661
*** No convergence -- monoMDS stopping criteria:
13: no. of iterations >= maxit
1: stress < smin
6: stress ratio > sratmax
Square root transformation
Wisconsin double standardization
Run 0 stress 0.00644259
Run 1 stress 0.001327398
... New best solution
... Procrustes: rmse 0.1068776 max resid 0.1493299
Run 2 stress 0.000654329
... New best solution
... Procrustes: rmse 0.06375063 max resid 0.1025383
Run 3 stress 0.01031367
Run 4 stress 0.002635087
Run 5 stress 0.005949759
Run 6 stress 0.003828015
Run 7 stress 9.904256e-05
... New best solution
... Procrustes: rmse 0.1479827 max resid 0.2950912
Run 8 stress 0.0004453573
... Procrustes: rmse 0.0631433 max resid 0.09089009
Run 9 stress 0.000133494
... Procrustes: rmse 0.02749027 max resid 0.03915047
Run 10 stress 9.777086e-05
... New best solution
... Procrustes: rmse 0.1450925 max resid 0.2926526
Run 11 stress 0.0001565034
... Procrustes: rmse 0.1435442 max resid 0.2392662
Run 12 stress 0.001407042
Run 13 stress 0.0002049246
... Procrustes: rmse 0.03291418 max resid 0.05021331
Run 14 stress 0.0001726277
... Procrustes: rmse 0.1432306 max resid 0.2399713
Run 15 stress 0.002818962
Run 16 stress 0.001279359
Run 17 stress 0.003963784
Run 18 stress 0.000833141
Run 19 stress 0.009254673
Run 20 stress 0.009023119
*** No convergence -- monoMDS stopping criteria:
18: no. of iterations >= maxit
2: stress < smin
OTUs
----------------------------
Call:
metaMDS(comm = otu.t, distance = "bray", k = 3, try = 10, display = c("sites"), choices = c(1, 2), type = "t", shrink = FALSE)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(otu.t))
Distance: bray
Dimensions: 3
Stress: 9.69273e-05
Stress type 1, weak ties
Two convergent solutions found after 10 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(otu.t))'
Phylum
----------------------------
Call:
metaMDS(comm = phylum.t, distance = "bray", k = 3, try = 10, display = c("sites"), choices = c(1, 2), type = "t", shrink = FALSE)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(phylum.t))
Distance: bray
Dimensions: 3
Stress: 5.792227e-06
Stress type 1, weak ties
No convergent solutions - best solution after 20 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(phylum.t))'
Class
----------------------------
Call:
metaMDS(comm = class.t, distance = "bray", k = 3, try = 10, display = c("sites"), choices = c(1, 2), type = "t", shrink = FALSE)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(class.t))
Distance: bray
Dimensions: 3
Stress: 0.001418859
Stress type 1, weak ties
Two convergent solutions found after 10 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(class.t))'
Order
----------------------------
Call:
metaMDS(comm = order.t, distance = "bray", k = 3, try = 10, display = c("sites"), choices = c(1, 2), type = "t", shrink = FALSE)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(order.t))
Distance: bray
Dimensions: 3
Stress: 0.02217476
Stress type 1, weak ties
Two convergent solutions found after 10 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(order.t))'
Family
----------------------------
Call:
metaMDS(comm = family.t, distance = "bray", k = 3, try = 10, display = c("sites"), choices = c(1, 2), type = "t", shrink = FALSE)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(family.t))
Distance: bray
Dimensions: 3
Stress: 8.579538e-05
Stress type 1, weak ties
No convergent solutions - best solution after 20 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(family.t))'
Genus
----------------------------
Call:
metaMDS(comm = genus.t, distance = "bray", k = 3, try = 10, display = c("sites"), choices = c(1, 2), type = "t", shrink = FALSE)
global Multidimensional Scaling using monoMDS
Data: wisconsin(sqrt(genus.t))
Distance: bray
Dimensions: 3
Stress: 9.777086e-05
Stress type 1, weak ties
No convergent solutions - best solution after 20 tries
Scaling: centring, PC rotation, halfchange scaling
Species: expanded scores based on 'wisconsin(sqrt(genus.t))'
Figure X. Sherperd and non-metric multidimensional scaling plot. Green oints represent samples and red points represent OTU or species. Similar samples are ordinated together. Stress values are shown at the botthom of ordination plot.
Figure x: The circular phylograms (A), unrooted cladogram (B), and the rectangular phylograms (C) display the relationships of the 360 samples used in the case study. Female (red) and male (blue) linked with sequence counts showing the proportion of the number of classified (green) and unclassified (red) displayed on a pie chart followed by the phyla abundance (heatmap) and species richness bar chart showing the observed (green) and estimated (maroon) richness. A portion of the tree (D) is enlarged to show some details.
R version 3.5.2 (2018-12-20)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.4
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] NbClust_3.0 iNEXT_2.0.19 goeveg_0.4.2 vegan_2.5-4
[5] permute_0.9-4 scales_1.0.0 ggpubr_0.2 magrittr_1.5
[9] dplyr_0.8.0.1 reshape2_1.4.3 funModeling_1.7 Hmisc_4.2-0
[13] ggplot2_3.1.0 Formula_1.2-3 survival_2.43-3 lattice_0.20-38
loaded via a namespace (and not attached):
[1] maps_3.3.0 splines_3.5.2 dotCall64_1.0-0
[4] gtools_3.8.1 moments_0.14 assertthat_0.2.1
[7] latticeExtra_0.6-28 pander_0.6.3 yaml_2.2.0
[10] slam_0.1-45 corrplot_0.84 pillar_1.3.1
[13] backports_1.1.3 glue_1.3.1 digest_0.6.18
[16] RColorBrewer_1.1-2 checkmate_1.9.1 colorspace_1.4-1
[19] cowplot_0.9.4 htmltools_0.3.6 Matrix_1.2-15
[22] plyr_1.8.4 tm_0.7-6 pkgconfig_2.0.2
[25] purrr_0.3.2 gdata_2.18.0 htmlTable_1.13.1
[28] tibble_2.1.1 mgcv_1.8-27 withr_2.1.2
[31] ROCR_1.0-7 nnet_7.3-12 lazyeval_0.2.1
[34] NLP_0.2-0 crayon_1.3.4 evaluate_0.13
[37] nlme_3.1-137 MASS_7.3-51.1 gplots_3.0.1.1
[40] xml2_1.2.0 foreign_0.8-71 tools_3.5.2
[43] data.table_1.12.0 hms_0.4.2 stringr_1.4.0
[46] munsell_0.5.0 cluster_2.0.7-1 entropy_1.2.1
[49] compiler_3.5.2 caTools_1.17.1.1 rlang_0.3.4
[52] grid_3.5.2 rstudioapi_0.10 spam_2.2-1
[55] htmlwidgets_1.3 bitops_1.0-6 base64enc_0.1-3
[58] labeling_0.3 rmarkdown_1.12 gtable_0.2.0
[61] R6_2.4.0 gridExtra_2.3 knitr_1.22
[64] readr_1.3.1 KernSmooth_2.23-15 stringi_1.4.3
[67] parallel_3.5.2 Rcpp_1.0.1 fields_9.6
[70] rpart_4.1-13 acepack_1.4.1 tidyselect_0.2.5
[73] xfun_0.6